An SRN Based Approach for Performance Evaluation of Network Layer in Mobile Ad hoc Networks
Subject Areas : Wireless Network
meisam Yadollahzadeh tabari
1
*
,
Ali A Pouyan
2
1 - Babol Branch, Islamic Azad University
2 - shahrood university of thechnology
Keywords: Mobile ad Hoc Network, , Stochastic Reward Net, , Performance Evaluation, , Modeling, ,
Abstract :
The application of mobile ad hoc networks (MANET) in emergency and critical cases needs a precise and formal performance evaluation of these networks. Traditional simulation-based performance evaluators like NS-2 and OPNET usually need a considerable time for producing high level performance metrics. Also there is no theoretical background for mentioned simulators, too. In this research, we propose a framework for performance evaluation of mobile ad hoc networks. The presented framework points to the network layer of MANETs using SRN (Stochastic Reward Nets) modeling tool as variation of generalized stochastic Petri net (GSPN). Based on decomposition technique it encompasses two separate models: one for analysis of data flowing process and the other for modeling routing process ; supposing AODV as a routing protocol that is worked out. To verify the presented model, an equivalence-based method is applied. The proposed SRN model has been quantified by deriving two performances metrics as Packet Delivery Ratio (PDR) and End-to-end Delay. Both metrics are also compared to the value obtained from NS-2 simulator versus different number of nodes and four packet generation rates. The results show the obtained values from presented SRN model well matched to the values generated from NS-2 simulator with a considerable lesser execution time.
[1] Tabari MY, Hassanpour H, Pouyan A, Saleki S. Proposing a light weight semi-distributed IDS for mobile ad-hoc network based on nodes' mode. In6th International Symposium on Telecommunications (IST) 2012 Nov 6 (pp. 948-953). IEEE.
[2] Younes O, Thomas N. Modelling and performance analysis of multi-hop ad hoc networks. Simulation Modelling Practice and Theory. 2013 Nov 1;38:69-97.
[3] Pouyan A, Yadollahzadeh Tabari M. Estimating reliability in mobile ad-hoc networks based on Monte Carlo simulation. International Journal of Engineering. 2014 Jan 21;7(5):739-46.
[4] "The Network Simulator ns2," available at http://www.isi.edu/nsnam/ns/.
[5] "OPNET Modeler," available at http://www.opnet.com.
[6] Zeng X, Bagrodia R, Gerla M. GloMoSim: a library for parallel simulation of large-scale wireless networks. InProceedings. Twelfth Workshop on Parallel and Distributed Simulation PADS'98 (Cat. No. 98TB100233) 1998 May 26 (pp. 154-161). IEEE.
[7] Kostin A, Oz G, Haci H. Performance study of a wireless mobile ad hoc network with orientation‐dependent internode communication scheme. International Journal of Communication Systems. 2014 Feb;27(2):322-40.
[8] Pouyan AA, Yadollahzadeh Tabari M. FPN‐SAODV: using fuzzy petri nets for securing AODV routing protocol in mobile Ad hoc network. International Journal of Communication Systems. 2017 Jan 10;30(1):e2935.
[9] Masri A, Bourdeaud'Huy T, Toguyeni A. Performance analysis of IEEE 802.11 b wireless networks with object oriented Petri nets. Electronic Notes in Theoretical Computer Science. 2009 Jul 13;242(2):73-85.
[10] Marsan MA, Balbo G, Conte G, Donatelli S, Franceschinis G. Modelling with generalized stochastic Petri nets. John Wiley & Sons, Inc.; 1994 Oct 1.
[11] Tang Y, Chen L, He KT, Jing N. SRN: an extended Petri-net-based workflow model for Web service composition. InProceedings. IEEE International Conference on Web Services, 2004. 2004 Jul 6 (pp. 591-599). IEEE.
[12] German R, Heindl A. Performance evaluation of IEEE 802.11 wireless LANs with stochastic Petri nets. InProceedings 8th International Workshop on Petri Nets and Performance Models (Cat. No. PR00331) 1999 (pp. 44-53). IEEE.
[13] Zhang C, Zhou M. A stochastic Petri net-approach to modeling and analysis of ad hoc network. InInternational Conference on Information Technology: Research and Education, 2003. Proceedings. ITRE2003. 2003 Aug 11 (pp. 152-156). IEEE.
[14] Xiong C, Murata T, Tsai J. Modeling and simulation of routing protocol for mobile ad hoc networks using colored petri nets. InProceedings of the conference on Application and theory of petri nets: formal methods in software engineering and defence systems-Volume 12 2002 Jun 1 (pp. 145-153). Australian Computer Society, Inc.
[15] Ciardo G, Cherkasova L, Kotov V, Rokicki T. Modeling a scalable high-speed interconnect with stochastic Petri nets. InProceedings 6th International Workshop on Petri Nets and Performance Models 1995 Oct 3 (pp. 83-92). IEEE.
[16] Kostin A, Oz G, Haci H. Performance study of a wireless mobile ad hoc network with orientation-dependent inter-node communication links. In2009 24th International Symposium on Computer and Information Sciences 2009 Sep 14 (pp. 316-321). IEEE.
[17] Chiang TC, Tai CF, Hou TW. A knowledge-based inference multicast protocol using adaptive fuzzy Petri nets. Expert Systems with Applications. 2009 May 1;36(4):8115-23.
[18] Younes O, Thomas N. A path connection availability model for MANETs with random waypoint mobility. InComputer Performance Engineering 2012 Jul 30 (pp. 111-126). Springer, Berlin, Heidelberg.
[19] Ciardo G, Muppala J, Trivedi K. SPNP: stochastic Petri net package. InProceedings of the Third International Workshop on Petri Nets and Performance Models, PNPM89 1989 Dec 11 (pp. 142-151). IEEE.
[20] Younes O, Thomas N. An SRN model of the IEEE 802.11 DCF MAC protocol in multi-hop ad hoc networks with hidden nodes. The Computer Journal. 2011 Jun;54(6):875-93.
[21] Yadollahzadeh Tabari M, Pouyan AA. Misbehavior analysis of IEEE 802.11 MAC layer in mobile ad hoc network using stochastic reward nets. International Journal of Communication Systems. 2017 Nov 10;30(16):e3385.
[22] Soltani MD, Purwita AA, Zeng Z, Haas H, Safari M. Modeling the random orientation of mobile devices: Measurement, analysis and LiFi use case. IEEE Transactions on Communications. 2019 Mar;67(3):2157-72.
[23] Bettstetter C. On the connectivity of ad hoc networks. The computer journal. 2004 Jan 1;47(4):432-47.
[24] Xu J. On the fundamental tradeoffs between routing table size and network diameter in peer-to-peer networks. InIEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No. 03CH37428) 2003 Mar 30 (Vol. 3, pp. 2177-2187). IEEE.
[25] Hu X, Jiao L, Li Z. Modelling and performance analysis of IEEE 802.11 DCF using coloured Petri nets. The Computer Journal. 2016 Oct; 59(10):1563-80.
[26] Erbas F, Kyamakya K, Jobmann K. Modelling and performance analysis of a novel position-based reliable unicast and multicast routing method using coloured Petri nets. In2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No. 03CH37484) 2003 Oct 6 (Vol. 5, pp. 3099-3104). IEEE.
[27] Hieu TD, Choi SG. Simulation modeling and analysis of the hop count distribution in cognitive radio ad-hoc networks with shadow fading. Simulation Modelling Practice and Theory. 2016 Dec 1;69:43-54.
[28] Ciardo G, Trivedi KS. A decomposition approach for stochastic Petri net models. InProceedings of the Fourth International Workshop on Petri Nets and Performance Models PNPM91 1991 Dec 2 (pp. 74-83). IEEE.